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Where GX Cloud fits in

In the landscape of data technology, where does GX Cloud go?

Erin Kapp
October 01, 2024
silver puzzle pieces partially assembled and partially piled, with a single orange piece that has the GX logo on it in focus

Do we need to reiterate the importance of data to a modern organization? No. We’re all on the same page by now.

But making the data happen and putting it to work effectively can be a real Wild West scenario. And data and analytics tools have proliferated exponentially.

The result: you’re just trying to solve a problem or fill a gap in your processes… and instead you end up adrift in a sea of revolutionary ML-powered platforms promising to enable your AI-ready data-driven future. In the cloud, obviously.

So plain and simple, here’s what GX Cloud does for you and how it relates to other kinds of data technology.

GX Cloud + data sources

Data sources: how any of this is even possible.

GX Cloud has a watchdog role for data sources. Use GX Cloud to make sure that the data coming to rest in your storage has been verified as high quality and suitable for its intended uses. 

What are its intended uses? What does ‘high quality’ mean? That’s something your business and technical teams collaborate to specify, together, in GX Cloud.

How will ‘high quality’ be verified? Using the tests that your data’s stakeholders—the relevant business and data teams—build in GX Cloud. 

How is the verification carried out? GX Cloud executes the tests (Expectations) that your data and business teams built. 

Where is the verification carried out? GX Cloud orchestrates the execution of your Expectations in the data source where it already is.

GX Cloud’s tests are extremely expressive, so you can build in some serious nuance while Expectations remain perfectly comprehensible to a newcomer.

In other words: GX Cloud’s tests—aka Expectations— aren’t just the operational mechanism you use to verify a data source’s quality. They’re also the educational knowledge center that documents a data source’s quality standards.

GX Cloud + ingestion technologies

Ingestion technologies: getting data from there to here.

GX Cloud augments your ingestion technology. Use GX Cloud to make sure that only the good stuff actually gets ingested.

What’s ‘the good stuff’? That’s defined by your data and business teams as they collaborate to build quality tests (Expectations) in GX Cloud.

How is only the good stuff ingested? GX Cloud executes the tests that identify the good stuff vs the bad stuff. With the bad stuff identified, GX Cloud can trigger actions that prevent low-quality data from being ingested and/or divert it to a separate location for remediation.

GX Cloud + orchestration

Orchestrators: pulling all the strings.

GX Cloud calls on orchestrators to react to its test results, and can be called upon in turn. Use GX Cloud to ensure high-quality vs low-quality data is treated differently and appropriately by your orchestrators.

How does GX Cloud identify high-quality vs low-quality data? With its tests, aka Expectations, which your data and business teams collaborated to build.

How can orchestrators react differently to high- vs low-quality data? GX Cloud indicates whether the data is high-quality at the dataset level and/or at the row level. An orchestrator can then take action to propagate or ingest high-quality data, reject or isolate low-quality data, or other appropriate action.

Does GX Cloud require a separate orchestrator in order to do anything useful with its monitoring results? No. GX Cloud has built-in orchestration capabilities that allow you to execute core orchestration functions natively. You can choose to use an external orchestrator if you prefer to do so.

GX Cloud + observability

Observability technologies: knowing the state of your data.

GX Cloud is observability technology. It focuses on proactive testing that checks for specific, known needs and requirements of the data.

How do the tests check for specific, known needs and requirements? Your technical and business teams work together in GX Cloud to define them.

How do the needs and requirements remain ‘known’ as the individuals who created them come and go? GX Cloud implements tests as highly-expressive Expectations, which document themselves to create a durable knowledge repository.

GX Cloud + governance and data catalogs

Governance and data catalogs: keeping track of what’s happening here.

GX Cloud is complementary to governance and data catalog technologies. Use GX Cloud to be confident that people can actually use the data that your catalogs and governance tools point them to.

How do you get confidence in your data? GX Cloud’s tests (Expectations) monitor your data against the specific, known needs and requirements that your data and business teams have collaborated to define.

GX Cloud + analytics and consumption

Analytics and consumption: the point of all this.

GX Cloud is a crucial prerequisite for analytics and consumption technologies. Use GX Cloud to ensure that you can trust the results that your analytics and consumption tools are producing.

Why can you trust your results? Because GX Cloud has verified that your data is suitable for its intended use—which includes its uses in these tools.

How does GX Cloud know what makes the data suitable? Your data and business teams have collaborated to determine that, using their collective experience from their respective areas of expertise.

How were your data and business teams able to collaborate effectively? Because GX Cloud provided an accessible, user-friendly SaaS interface where people can work together to create tests (Expectations) without needing any code.

How can you create effective data quality tests without code? GX Cloud’s tests, called Expectations, use plain language to define precisely what you expect your data to be.

How are the tests run? GX Cloud executes Expectations on your data in the location where your data already is.

What if an Expectation finds a problem? GX Cloud’s alerts can notify the relevant people immediately, and identify the problematic data to your orchestrators for isolation or rejection.

Because Expectations are expressive and context-rich, GX Cloud tells you which data is affected down to the individual columns and rows (if relevant), as well as the nature of the problem. Your data teams have the information they need to begin working on a fix right away.

Conclusion

That’s the rundown of how GX Cloud relates to other data technologies. Here’s the summary:

For data sources, GX Cloud makes sure that the data coming to rest in them has been verified as high quality and suitable for its intended uses. 

For ingestion tools, GX Cloud ensures that only data you actually want gets ingested.

For orchestrators, GX Cloud makes it easy to disseminate high-quality data while isolating low-quality data, and provides meaningful and information-rich test results for propagation to other systems and dashboards.

For your observability needs, GX Cloud implements proactive testing that checks for specific, known needs and requirements of the data.

For your governance and data catalog tools, GX Cloud provides monitoring and test results that allows people to make informed decisions about using the data that your governance tools direct them to.

For your analytics and data consumption, GX Cloud is a critical tool that ensures you can trust the results of your analyses and have confidence in the correctness of your operational data use.



Data teams across the globe are discovering how to trust their data with GX Cloud. To join them, watch our customer conversation or get started today.

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